From 56ff0edf102747ffc39d60f57a54385bba40267b Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Fri, 21 Apr 2017 10:45:31 +0000
Subject: [PATCH] Update Readme.md
---
README.md | 13 +++++++++----
1 files changed, 9 insertions(+), 4 deletions(-)
diff --git a/README.md b/README.md
index c8af82c..f833da9 100644
--- a/README.md
+++ b/README.md
@@ -12,7 +12,7 @@
|  |  https://arxiv.org/abs/1612.08242 |
|---|---|
-|  |  https://arxiv.org/abs/1612.08242 |
+|  |  https://arxiv.org/abs/1612.08242 |
|---|---|
@@ -112,7 +112,7 @@
5. If you want to build with CUDNN to speed up then:
- * download and install CUDNN: https://developer.nvidia.com/cudnn
+ * download and install **cuDNN 5.1 for CUDA 8.0**: https://developer.nvidia.com/cudnn
* add Windows system variable `cudnn` with path to CUDNN: https://hsto.org/files/a49/3dc/fc4/a493dcfc4bd34a1295fd15e0e2e01f26.jpg
@@ -136,13 +136,14 @@
`..\..\3rdparty\lib\x64\pthreadVC2.lib;cublas.lib;curand.lib;cudart.lib;cudnn.lib;%(AdditionalDependencies)`
- (right click on project) -> properties -> C/C++ -> Preprocessor -> Preprocessor Definitions
+`OPENCV;_TIMESPEC_DEFINED;_CRT_SECURE_NO_WARNINGS;GPU;WIN32;NDEBUG;_CONSOLE;_LIB;%(PreprocessorDefinitions)`
+
- open file: `\src\yolo.c` and change 3 lines to your OpenCV-version - `249` (for 2.4.9), `2413` (for 2.4.13), ... :
* `#pragma comment(lib, "opencv_core249.lib")`
* `#pragma comment(lib, "opencv_imgproc249.lib")`
* `#pragma comment(lib, "opencv_highgui249.lib")`
-`OPENCV;_TIMESPEC_DEFINED;_CRT_SECURE_NO_WARNINGS;GPU;WIN32;NDEBUG;_CONSOLE;_LIB;%(PreprocessorDefinitions)`
- compile to .exe (X64 & Release) and put .dll-s near with .exe:
`pthreadVC2.dll, pthreadGC2.dll` from \3rdparty\dll\x64
@@ -168,7 +169,9 @@
5. Run command: `type 2007_train.txt 2007_val.txt 2012_*.txt > train.txt`
-6. Start training by using `train_voc.cmd` or by using the command line: `darknet.exe detector train data/voc.data yolo-voc.cfg darknet19_448.conv.23`
+6. Set `batch=64` and `subdivisions=8` in the file `yolo-voc.cfg`: [link](https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/yolo-voc.cfg#L3)
+
+7. Start training by using `train_voc.cmd` or by using the command line: `darknet.exe detector train data/voc.data yolo-voc.cfg darknet19_448.conv.23`
If required change pathes in the file `build\darknet\x64\data\voc.data`
@@ -186,6 +189,8 @@
1. Create file `yolo-obj.cfg` with the same content as in `yolo-voc.cfg` (or copy `yolo-voc.cfg` to `yolo-obj.cfg)` and:
+ * change line batch to [`batch=64`](https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/yolo-voc.cfg#L3)
+ * change line subdivisions to [`subdivisions=8`](https://github.com/AlexeyAB/darknet/blob/master/build/darknet/x64/yolo-voc.cfg#L4)
* change line `classes=20` to your number of objects
* change line #224 from [`filters=125`](https://github.com/AlexeyAB/darknet/blob/master/cfg/yolo-voc.cfg#L224) to `filters=(classes + 5)*5` (generally this depends on the `num` and `coords`, i.e. equal to `(classes + coords + 1)*num`)
--
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